Manager, Data Scientist

Ensure all AI solution development is in line with industry standards for data management and privacy compliance including the collection, use, storage, access, retention, output, reporting, and quality of data at Mastercard
Adopt a pragmatic approach to AI, capable of articulating complex technical requirements in a manner this is simple and relevant to stakeholder use cases
Gather relevant information to define the business problem interfacing with global stakeholders
Creative thinker capable of linking AI methodologies to identified business challenges
Identify commonalities amongst use cases enabling a microservice approach to scaling AI at Mastercard, building reusable, multi-purpose models
Develop AI/ML solutions/applications leveraging the latest industry and academic advancements
Leverage open and closed source technologies to solve business problems
Ability to work cross-functionally, and across borders drawing on a broader team of colleagues to effectively execute the AI agenda
Partner with technical teams to implement developed solutions/applications in production environment
Support a learning culture continuously advancing AI capabilities

All About You

Experience
8+ years of experience in the Data Sciences field with a focus on AI strategy and execution and developing solutions from scratch
Demonstrated passion for AI competing in sponsored challenges such as Kaggle
Previous experience with or exposure to:
oDeep Learning algorithm techniques, open source tools and technologies, statistical tools, and programming environments such as Python, R, and SQL
oBig Data platforms such as Hadoop, Hive, Spark, GPU Clusters for deep learning
oClassical Machine Learning Algorithms like Logistic Regression, Decision trees, Clustering (K-means, Hierarchical and Self-organizing Maps), TSNE, PCA, Bayesian models, Time Series ARIMA/ARMA, Recommender Systems - Collaborative Filtering, FPMC, FISM, Fossil
oDeep Learning algorithm techniques like Random Forest, GBM, KNN, SVM, Bayesian, Text Mining techniques, Multilayer Perceptron, Neural Networks - Feedforward, CNN, LSTM s GRU s is a plus. Optimization techniques - Activity regularization (L1 and L2), Adam, Adagrad, Adadelta concepts; Cost Functions in Neural Nets - Contrastive Loss, Hinge Loss, Binary Cross entropy, Categorical Cross entropy; developed applications in KRR, NLP, Speech and Image processing
oDeep Learning frameworks for Production Systems like Tensorflow, Keras (for RPD and neural net architecture evaluation), PyTorch and Xgboost, Caffe, and Theono is a plus
Exposure or experience using collaboration tools such as:
oConfluence (Documentation)
oBitbucket/Stash (Code Sharing)
oShared Folders (File Sharing)
oALM (Project Management)
Knowledge of payments industry a plus
Experience with SAFe (Scaled Agile Framework) process is a plus

Effectiveness
Effective at managing and validating assumptions with key stakeholders in compressed timeframes, without hampering development momentum
Capable of navigating a complex organization in a relentless pursuit of answers and clarity
Enthusiasm for Data Sciences embracing the creative application of AI techniques to improve an organizations effectiveness
Ability to understand technical system architecture and overarching function along with interdependency elements, as well as anticipate challenges for immediate remediation
Ability to unpack complex problems into addressable segments and evaluate AI methods most applicable to addressing the segment
Incredible attention to detail and focus instilling confidence without qualification in developed solutions

Core Capabilities
Strong written and oral communication skills
Strong project management skills
Concentration in Computer Science
Some international travel required